Development of an FPGA and MCU based Stack-able Processing platform incorporated with on-board compute module for Real-time processing applications

Wang, Teng (2017) Development of an FPGA and MCU based Stack-able Processing platform incorporated with on-board compute module for Real-time processing applications. Masters thesis, Memorial University of Newfoundland.

[English] PDF - Accepted Version Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission. Download (43MB)

Abstract

The focus of this thesis is to develop an FPGA and MCU-based stackable processing platform incorporated with an on-board computer module for real-time processing applications. The goal is to deliver a compact-sized hardware platform with extensible capabilities to provide high-speed, parallel computing with low power consumption. This hardware platform is named ioNeurons and consists of three module types: processing modules, sensing modules, and interface modules. The ioNeurons ecosystem design is based on combining individual strengths into highly adaptable and powerful solutions. The processing modules are stackable in no particular order, allowing the ability to match multiple modules’ individual capabilities to the project’s needs. Developers can assign tasks to multiple processing modules according to the different real-time requirements. The implementation of a small-scale quadrotor helicopter is introduced as an application of this hardware platform.

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